GenAI Engineer at BDIPlus

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

17 Sep, 26

Salary

120000.0

Posted On

19 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Generative AI, Large Language Models, Retrieval-Augmented Generation, Python, FastAPI, Flask, SQL, LLMOps, RAG System Design, Model Fine-tuning, Backend Engineering, Data Engineering, Vector Search, API Development, Prompt Engineering, Cloud Platforms

Industry

Information Technology & Services

Description

ABOUT US: BDIPlus is a US-based consulting and Customer Data Platform (CDP) company specializing in technology transformation for the Financial Services and Insurance sectors. We help enterprises turn complex data into actionable insights, enabling smarter decisions, greater efficiency and accelerated growth. BDIPlus is currently looking for a Generative AI Engineer for our offices located in New York, NY. JOB OVERVIEW: As a Generative AI Engineer at BDIPlus, you will be responsible for designing, developing and deploying Generative AI solutions that enhance our core product platforms and client implementations. You will work closely with engineering, data science, and infrastructure teams to build scalable AI-driven applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), model fine-tuning, and reinforcement learning approaches. This role is ideal for someone who is passionate about building real-world GenAI applications and bringing them into production, while continuously improving performance, reliability and user outcomes. WHAT YOU'LL DO: * Deliver GenAI solutions end-to-end * Own technical design and implementation of GenAI applications from discovery through production handoff. * Build APIs/services that integrate with enterprise systems and analytics platforms. * Implement enterprise-grade RAG * Design ingestion pipelines for internal content (PDFs, policies, research, dashboards, ticketing, wikis). * Build retrieval systems with hybrid search, filtering, re-ranking, query rewriting, and context optimization. * Implement permission-aware retrieval aligned to entitlements and data access policies. * Establish evaluation and quality controls. * Define metrics for retrieval quality and answer grounding (faithfulness, citation accuracy, coverage). * Create golden datasets, regression tests, and automated evaluation harnesses. * Operationalize GenAI (LLMOps) * Instrument observability (latency, cost, token usage, error rates) and implement safe rollout patterns. * Implement caching, rate limiting, fallbacks, and incident-ready operational practices. * Partner across teams to land solutions * Collaborate with business owners to translate requirements into workable designs. * Work with Security/Compliance to embed guardrails, auditability, and privacy controls. * Provide clear documentation and implementation playbooks to enable internal teams post-engagement. Required Skills & Qualifications: * Education: Master's degree or equivalent experience required; PhD a plus * 3+ years in software engineering, data engineering, ML engineering, or applied AI, including recent GenAI delivery in production. * Demonstrated expertise in RAG system design and optimization, including: * chunking + metadata enrichment, hybrid search, re-ranking, retrieval evaluation * grounding/citations and hallucination mitigation patterns * Strong Python and backend engineering skills (FastAPI/Flask), plus strong SQL. * Experience working in regulated or security-conscious environments, with knowledge of: * access controls/entitlements, data privacy, logging/audit trails, secure SDLC practices * Proven ability to work effectively as an IC consultant: * communicate architecture decisions clearly * influence cross-functional stakeholders without direct authority * produce high-quality documentation and handoff materials Preferred / Nice to Have: * Fine-tuning experience (SFT, LoRA/QLoRA) and familiarity with preference optimization concepts (DPO/RLHF) * Vector/hybrid search platforms: Elasticsearch/OpenSearch vector, FAISS, Pinecone, Weaviate, Milvus * LLMOps tooling: MLflow/W&B, OpenTelemetry, prompt registries, evaluation frameworks * Cloud + platform: AWS/Azure/GCP, Docker/Kubernetes, Terraform * Finance domain familiarity (risk, compliance, research workflows, client communications) Tools & Technologies * LLM frameworks: LangChain, LlamaIndex, Semantic Kernel (optional) * Vector/hybrid search: (insert your preferred tools) * Data: (Snowflake/Databricks/warehouse), event pipelines, document stores * Observability: logging/tracing/metrics, dashboards, alerting OUR PURPOSE & CULTURE AT BDIPLUS: Our mission is to help enterprises utilize their resources more efficiently, implement effective information management and empower them with richer insights and intelligence. We are driven by a single purpose: empower technology transformation. We are passionate about creating foundational technology platforms for enterprise data and information management. Our employees are at the heart of the work we do at BDIPlus, and we are committed to encouraging and celebrating innovation, creativity and hard work among our team members. ---------------------------------------- WORKING AT BDIPLUS OFFERS: * A diverse, fun, intelligent and innovative team. * Full health and commuter benefits. * Competitive salary. * Paid time off, sick leave and most national holidays. * Visa sponsorship. * An environment where creative thinking is encouraged and innovation is a driving force in everything we do.

Responsibilities

Design, develop, and deploy end-to-end Generative AI solutions and enterprise-grade RAG systems to enhance core product platforms. Collaborate with cross-functional teams to implement LLMOps, observability, and security guardrails for production-ready AI applications.